Zobrazeno 1 - 10
of 544
pro vyhledávání: '"Meirui An"'
Federated learning (FL) is a learning paradigm that enables collaborative training of models using decentralized data. Recently, the utilization of pre-trained weight initialization in FL has been demonstrated to effectively improve model performance
Externí odkaz:
http://arxiv.org/abs/2410.23660
Despite recent progress in enhancing the privacy of federated learning (FL) via differential privacy (DP), the trade-off of DP between privacy protection and performance is still underexplored for real-world medical scenario. In this paper, we propos
Externí odkaz:
http://arxiv.org/abs/2307.12542
Cross-silo federated learning (FL) enables the development of machine learning models on datasets distributed across data centers such as hospitals and clinical research laboratories. However, recent research has found that current FL algorithms face
Externí odkaz:
http://arxiv.org/abs/2307.10507
Autor:
Jiang, Meirui, Roth, Holger R, Li, Wenqi, Yang, Dong, Zhao, Can, Nath, Vishwesh, Xu, Daguang, Dou, Qi, Xu, Ziyue
How to ensure fairness is an important topic in federated learning (FL). Recent studies have investigated how to reward clients based on their contribution (collaboration fairness), and how to achieve uniformity of performance across clients (perform
Externí odkaz:
http://arxiv.org/abs/2303.16520
Publikováno v:
ICT Express, Vol 10, Iss 4, Pp 909-915 (2024)
Mobile learning allows for an interactive way of learning through devices like smartphones. However, current methods usually rely on pre-set situations and struggle to recognize new contexts when they come up during testing. To solve this, we suggest
Externí odkaz:
https://doaj.org/article/c581d2ce53b34a9dbd2d6b5e830fd60b
Domain generalization (DG) has been a hot topic in image recognition, with a goal to train a general model that can perform well on unseen domains. Recently, federated learning (FL), an emerging machine learning paradigm to train a global model from
Externí odkaz:
http://arxiv.org/abs/2210.00912
Publikováno v:
Eco-Environment & Health, Vol 3, Iss 1, Pp 80-88 (2024)
Disrupting effects of pollutants on symbiotic microbiota have been regarded as an important mechanism of host toxicity, with most current research focusing on the intestinal microbiota. In fact, the epidermal microbiota, which participates in the nut
Externí odkaz:
https://doaj.org/article/c890e174a3b64eaf81c53d6e8e356a2f
Despite recent progress on semi-supervised federated learning (FL) for medical image diagnosis, the problem of imbalanced class distributions among unlabeled clients is still unsolved for real-world use. In this paper, we study a practical yet challe
Externí odkaz:
http://arxiv.org/abs/2206.13079
Autor:
Yilin Jiang, Xun Wei, Meirui Zhu, Xiaoyan Zhang, Qingping Jiang, ZiXiao Wang, Yanyong Cao, Xueli An, Xiangyuan Wan
Publikováno v:
Current Plant Biology, Vol 40, Iss , Pp 100383- (2024)
Given global agricultural challenges such as population growth, climate change, and limitations on resources and the environment, as well as increasing diversity in breeding goals, relying on traditional breeding methods is inadequate to provide food
Externí odkaz:
https://doaj.org/article/2da45088e3cf41df9f4eb37886d9c03c
Publikováno v:
Cancer Control, Vol 31 (2024)
Introduction The role of SMU1 in DNA replication and RNA splicing is well-established, yet its specific function and dysregulated mechanisms in gastric cancer (GC) remain inadequately elucidated. This study seeks to investigate the potential oncogeni
Externí odkaz:
https://doaj.org/article/e965a045d92b48bd91cd83c016e1ac05